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Topic 5c – Data validation case study: monitoring emissions from fires

How do we validate satellite measurements?
So here we can see displayed multiple years of data from the MODIS instrument on board the NASA Terra satellite. And what we’re displaying here is the location of active fires across the planet. And you can see, for example, in Africa fires are migrating from north to south and back again during the different seasons of the year. This is the only way that we can get information on this sort of scale regularly updated. Earth observation is the only approach that can provide that view.
And information on fires like this are very useful, for example, for atmospheric scientists who want to know the role of biomass burning in placing material into the atmosphere– be it carbon dioxide, other gases like carbon monoxide, or aerosols. Now, how do we really know that this information is actually correct? We can use other satellites– for example the European Meteosat satellite here– that provides a much higher temporal resolution. So MODIS images every place on the planet for a few times a day, whereas Meteosat images Africa and Europe and a little part of bits of South America every 15 minutes. So it provides a much higher temporal resolution because of its geostationary position.
And you can see here that in July, most of the fires across Africa are located in southern Africa for example. The conditions are such in southern Africa that fires are very prevalent– particularly during the day. At night, it’s cooler. There’s generally less wind and high humidity. So fires die out. And you can see here that the pulsing of fires in the day and night in this speeded-up view. And we can use this sort of information to estimate the amount of carbon being emitted by these fires into the atmosphere. And here we’ve got a graph of that over the 24-hour period. However, even though we can see in more detail here, we still can’t tell how accurate this information is.
And what we need to use to assess that is some form of validation. And the way we do that is usually go into the field and make similar measurements to those from satellites, but using alternative methods. Here you can see a video from a field campaign we’ve recently conducted in Kruger National Park, South Africa, where they have a prescribed burning programme where they burn large areas of land multiple times per year. It’s for an ecological experiment, but we were able to use that to light the fires at the time the satellites were overpassing.
And here you can see the view from a helicopter where somebody’s using an infrared camera here which records at similar wavelengths of light to those that the satellite instruments record at. And we’re actually recording the thermal energy emissions from that fire. Later on, those will be compared to the simultaneous measurements made by the satellite, and that will provide the validation.
We’re here in Kruger National Park, South Africa, as part of a field validation campaign. And there’s actually a whole group of scientists working here who are trying to validate active fire products. And you can see behind me this area of woody Savannah. This is actually going to be burnt tomorrow. And at the moment, some of the scientists are here making some pre-fire measurements. So if we go over here, you can see some equipment set up in this plot– a scanning system on top of the truck here. And this is Mark who’s controlling it. Can you tell us a little bit about this piece of equipment? Sure, yeah.
So here we’ve got a LIDAR laser system that we’re using to scan this plot of vegetation. We’ll be able to create a three-dimensional vegetation model of the area. And then tomorrow, after we’ve carried out the burn, we’ll come back, and we’ll create another model of the area with less vegetation. And we can subtract the second model from the first. And then we can get an impression of the biomass consumed in the fire. That will be compared to data from a thermal imaging system that’s being carried by helicopter. That gives you measurements of the heat output of the fire– the rate of energy output. It’s basically a series of experimental burn plots. This is one here.
And these plots are burned every year for various scientific purposes. Essentially, we’re exploiting this opportunity, because we know exactly when this plot is going to be burned. So we’re actually going to time the fire tomorrow with a satellite overpass so that the data we collect from the thermal imaging system on the helicopter can actually be compared to that from the satellite to see how well they match together.
So we know the size and the intensity of the fire from this imagery we collect from the helicopter. And at the same time, we can see whether the satellite’s actually identified that as a fire successfully or not. You can see I’m standing in a blackened area here. Well, about half an hour ago, it looked something like this grassy, woody area over here. And the personnel of Kruger National Park actually use experimental burning like this for a variety of purposes. And we’re just making use of that programme to perform this validation activity.
In this video, Professor Martin Wooster explains the importance and some of the basic principles of EO validation activities. He demonstrates, through a recent field study, an example of how validation of satellite active fire detections and the energy released from fires can be conducted, in a collaboration with the Scientific Services of Kruger National Park (SANParks), South Africa.
Earth observation is an extremely effective way of monitoring the Earth system, but it does not directly measure most of the Earth system properties we are interested in. Instead, the value of the targeted property (for example sea surface temperature (SST)) at the observed ground location corresponding to the satellite image ‘pixel’ under analysis, must be estimated from the measurements of electromagnetic energy arriving at different wavelengths from the area covered by that pixel.
For example, SST is usually estimated from an analysis of the different remotely sensed signals arriving from an area in a series of closely spaced thermal infrared wavebands (one waveband covering a relatively narrow range of wavelengths). As a result of the somewhat ‘indirect’ nature of such remotely sensed estimates of SST, it is extremely important that they are checked for their accuracy and precision, to ensure they meet specification and so that users of the data can be reliably informed of the uncertainties that are present (e.g. ‘the SST is known at this location to within ± 0.5 °C at 95% confidence’). This is one part of making such datasets ultimately well-suited for climate-related studies, where often trends occurring over time must be differentiated from other signals that might be present in the data.
Validation of remotely sensed information is therefore considered extremely important, and is often performed as part of the process of generating a new data product from satellite remote sensing. Validation often involves comparing the remotely sensed estimates at a particular location to those obtained via a trustable and independent ground-based measuring technique, which already has a known certainty, and can also involve comparison of two different and independent satellite-based estimates of the same parameter, perhaps taken at different spatial resolutions or with different measurement approaches.
Featured Educators:
  • Professor Martin Wooster
Additional on-screen contribution from Mark De Jong, King’s College London.
Thanks to Scientific Services, Kruger National Park, SANParks and colleagues from King’s College London for enabling filming at the South African field tests.
South Africa filming by Anna Turbelin.
Explore the Imagery, Data and Satellites:
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